Comparing deep neural networks against humans: object recognition when the signal gets weaker — mentioned by jsharf

Tue, 02 Jun 2020 04:10:07 GMT

I think that your definition of "NP-Hard" is incorrect. It would be better to instead say "Exponentially bound in required training data size" I say this because having a solid model of these terms is required when making "intuitive conjecture" about what is and isn't feasibly possible. Driving is NP-Hard? It would hint that humans have brains capable of computation more powerful than a turing machine. Which... suffice it to say we probably don't. I'm not aware of any proven algorithms that humans can compute which computers cannot. In images free of distortion and noise, computers were…

Paper and discussion history. A mention is not an endorsement.

Comparing deep neural networks against humans: object recognition when the signal gets weaker — mentioned by CamperBob2

Sat, 23 May 2020 07:14:33 GMT

Also we have a pattern and object detection computer behind our eyes that nothing on this planet even remotely comes close to. Not defending those who say that LIDAR isn't useful/important in self-driving cars, but this assertion is only marginally true today and won't be true at all for much longer. See https://arxiv.org/pdf/1706.06969 (2017), for instance.

Paper and discussion history. A mention is not an endorsement.

Comparing deep neural networks against humans: object recognition when the signal gets weaker · HackerPapers discussions

Comparing deep neural networks against humans: object recognition when the signal gets weaker — mentioned by jsharf

Comparing deep neural networks against humans: object recognition when the signal gets weaker — mentioned by CamperBob2